{"id":"W2179813712","doi":"10.3233/ao-2010-0081","title":"Open Biomedical Ontologies applied to prostate cancer","year":2011,"lang":"en","type":"article","venue":"Applied Ontology","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Computer science; Prostate cancer; Data science; Information retrieval; Cancer; Medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004735996,0.0006897673,0.0006535343,0.01032493,0.001947514,0.003568883,0.0009374923,0.000873915,0.00241106],"category_scores_gemma":[0.03026236,0.0003298806,0.001490599,0.01185322,0.001240366,0.004499055,0.004238859,0.001390813,0.0006745472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003195102,"about_ca_system_score_gemma":0.005422747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01633352,"about_ca_topic_score_gemma":0.01744833,"domain_scores_codex":[0.9919511,0.002909677,0.0009823199,0.0009641998,0.002785071,0.0004077437],"domain_scores_gemma":[0.9845877,0.00931119,0.001227188,0.00212874,0.00233868,0.0004064843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004781662,0.0004447649,0.03927684,0.004808838,0.0007264775,0.002037365,0.005952268,0.03030632,0.01796366,0.2139274,0.02361509,0.6604628],"study_design_scores_gemma":[0.0001025158,0.0001574081,0.04171674,0.002328954,0.0007797586,0.002587493,0.003753828,0.09293292,0.02067629,0.2960285,0.5387457,0.0001899556],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1358533,0.01539998,0.7652349,0.008537282,0.0008437582,0.001198341,0.0238929,0.004795165,0.04424445],"genre_scores_gemma":[0.5650745,0.01203465,0.3780002,0.001914964,0.000306466,0.0006930194,0.0370084,0.0008051991,0.004162741],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01633352,"threshold_uncertainty_score":0.0324769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04574248426547053,"score_gpt":0.3102968715088134,"score_spread":0.2645543872433429,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}